The field of the invention is nuclear magnetic resonance angiography (MRA), and particularly, the reconstruction of an image from a three-dimensional array of NMR date acquired using a time-of-flight (TOF) or phase contrast method.
Magnetic resonance angiography has become a well accepted method for evaluating the vascular system and diagnosing vascular disease. This method involves the collection of NMR data which is sensitive to the movement of blood through the vascular system, but is relatively insensitive to the surrounding stationary tissues. There are two different methods used for providing such sensitivity: the time-of-flight method; and the phase contrast method. Time-of-flight methods such as those disclosed in U.S. Pat. Nos. 4,574,239; 4,532,473 and 4,516,582 rely on the time interval between the transverse excitation of spins and the acquisition of the resulting NMR signal to distinguish between moving and stationary spins. During the interval fresh spins move into the region from which the NMR signal is acquired and excited spins move out of the region. In contrast, the stationary spins remain fixed during the interval between RF excitation and data acquisition, with the result that the NMR signal produced by stationary spins is substantially different in magnitude from that produced by moving spins. When an image is reconstructed from such NMR signals, the image pixels which correspond to moving spins are much brighter with the result that the vascular system that transports rapidly moving blood is much brighter than the surrounding stationary, or slowly moving tissues.
The phase contrast methods for sensitizing the NMR signals to moving spins relies on the fact that the phase of the NMR signal produced by moving spins is different from the phase of NMR signals produced by stationary or slowly moving spins. As disclosed in U.S. Pat. Nos. 4,609,872; 4,683,431 and Re 32,701, phase contrast methods employ magnetic field gradients during the NMR pulse sequence which cause the phase of the resulting NMR signals to be modulated as a function of spin velocity. The phase of the NMR signals can, therefore, be used to control the contrast, or brightness, of the pixels in the reconstructed image. Since blood is moving relatively fast, the vascular system will appear brighter in the resulting image.
Regardless of the method used to acquire the motion sensitive NMR data, it is comprised of a 3-dimensional array of NMR data which indicates image brightness. This array may be acquired using a 3D NMR pulse sequence, or it may be acquired with 2D NMR pulse sequences applied to a set of adjacent slices. While images may be produced simply by selecting a set of these data points located in a cross section through the 3D array, such images have limited diagnostic value. This is because blood vessels usually do not lie in a single plane and such cross sectional images show only short pieces or cross sections of many vessels that happen to pass through the selected plane. Such images are useful when a specific location in a specific vessel is to be examined, but they are less useful as a means for examining the health of the vascular system and identifying regions that may be diseased.
For assessing overall blood vessel structure and health it is more useful to project the 3D array of NMR data into a single projection image to produce an angiogram-like picture of the vascular system. The most commonly used technique for doing this is to project a ray from each pixel in the projection image through the array of data points and select the data point which has the maximum value. The value selected for each ray is used to control the brightness of its corresponding pixel in the projection image. This method, referred to hereinafter as the "maximum pixel technique," is very easy to implement and it gives aesthetically pleasing images. However, because the maximum pixel technique utilizes only a small fraction of the vascular information embodied in the data set, much diagnostic information is lost. For example, only the brightest value encountered by the ray is used to represent information in the direction of the ray and if another equally bright value representing a second, overlapping vessel is present, this fact is lost in the process. The diagnostic importance of this information loss is illustrated in FIGS. 3A-3C, where FIG. 3A illustrates the image of two overlapping vessels produced by the maximum pixel technique, FIG. 3B represents one possible harmless interpretation of the image and FIG. 3C represents a second interpretation which indicates a vascular aneurysm. To resolve such ambiguities, it is common practice to reconstruct another projection image from a different angle. That is a time consuming and costly solution to the problem.
Another technique which is used to form a projection image and which retains more of the available information is what is referred to hereinafter as the "integration method". With this method the brightness of each projection image pixel is determined by the sum of all the data points along the projection ray. While this method does accurately show overlapping vessels and provide an indication of vessel narrowing in the projection direction, it yields an image in which the vessels are superimposed on an overwhelming background of stationary tissues. That is, the contrast between the background and vessels is substantially reduced and the evaluation of vessels, particularly small ones, becomes very difficult. Images produced by the integration method can be improved substantially simply by integrating only data points which exceed a user defined threshold value. However, if the threshold value is chosen too low, much of the background will be included and the image will be very noisy. On the other hand, if the threshold value is set too high, small vessels and the edges of larger vessels will be lost.
Yet another technique used to produce projection images uses a 3D region-growing method. The origins of the regions in the 3-D data set to be grown are operator determined. The grown regions are then blurred and thresholded to create a mask which includes voxels just outside the vessel edges, which may have been omitted in the region-growing process. This method gives a very smooth representation of the vasculature in which vessel edges are retained and vessel overlap can be deduced by use of visual cues which are included in the rendering process. The method, however, relies on connectivity. Therefore, vessels with signal dropout due to pathology or artifacts may be missed if the operator fails to place a seed before and after the region of signal loss. The 3D rendering is also computationally intense and is quite time consuming.